Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 746 745 507 813 592 278 534 558 52 51 699 701 288 754 846 609 904 484 945 526
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 526 507 904 NA 52 846 558 813 945 746 278 534 484 288 745 51 NA 592 699 754 701 609 NA
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 1 3 2 4 4 1 1 4 4 3
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "d" "z" "g" "t" "f" "N" "K" "Q" "V" "D"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 17 19
which( manyNumbersWithNA > 900 )
[1] 3 9
which( is.na( manyNumbersWithNA ) )
[1] 4 17 23
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 904 945
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 904 945
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 904 945
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "N" "K" "Q" "V" "D"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "d" "z" "g" "t" "f"
manyNumbers %in% 300:600
[1] FALSE FALSE TRUE FALSE TRUE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE TRUE
which( manyNumbers %in% 300:600 )
[1] 3 5 7 8 18 20
sum( manyNumbers %in% 300:600 )
[1] 6
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "large" "large" "large" NA "small" "large" "large" "large" "large" "large" "small" "large" "small" "small" "large" "small" NA "large" "large" "large"
[21] "large" "large" NA
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "large" "large" "large" "UNKNOWN" "small" "large" "large" "large" "large" "large" "small" "large" "small" "small" "large" "small"
[17] "UNKNOWN" "large" "large" "large" "large" "large" "UNKNOWN"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 526 507 904 NA 0 846 558 813 945 746 0 534 0 0 745 0 NA 592 699 754 701 609 NA
unique( duplicatedNumbers )
[1] 1 3 2 4
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 1 3 2 4
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 9
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 945
which.min( manyNumbersWithNA )
[1] 16
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 51
range( manyNumbersWithNA, na.rm = TRUE )
[1] 51 945
manyNumbersWithNA
[1] 526 507 904 NA 52 846 558 813 945 746 278 534 484 288 745 51 NA 592 699 754 701 609 NA
sort( manyNumbersWithNA )
[1] 51 52 278 288 484 507 526 534 558 592 609 699 701 745 746 754 813 846 904 945
sort( manyNumbersWithNA, na.last = TRUE )
[1] 51 52 278 288 484 507 526 534 558 592 609 699 701 745 746 754 813 846 904 945 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 945 904 846 813 754 746 745 701 699 609 592 558 534 526 507 484 288 278 52 51 NA NA NA
manyNumbersWithNA[1:5]
[1] 526 507 904 NA 52
order( manyNumbersWithNA[1:5] )
[1] 5 2 1 3 4
rank( manyNumbersWithNA[1:5] )
[1] 3 2 4 5 1
sort( mixedLetters )
[1] "d" "D" "f" "g" "K" "N" "Q" "t" "V" "z"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 6.5 3.0 9.0 6.5 3.0 3.0 9.0 3.0 9.0 3.0
rank( manyDuplicates, ties.method = "min" )
[1] 6 1 8 6 1 1 8 1 8 1
rank( manyDuplicates, ties.method = "random" )
[1] 7 1 8 6 2 3 9 5 10 4
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 -1.10228814 -0.98725768 -0.14996734 1.11902339 -0.03119318 0.91440077 -0.50491786 1.78671117
[14] -0.35495474 -0.24869741
round( v, 0 )
[1] -1 0 0 0 1 -1 -1 0 1 0 1 -1 2 0 0
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 -1.1 -1.0 -0.1 1.1 0.0 0.9 -0.5 1.8 -0.4 -0.2
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 -1.10 -0.99 -0.15 1.12 -0.03 0.91 -0.50 1.79 -0.35 -0.25
floor( v )
[1] -1 -1 0 0 1 -2 -1 -1 1 -1 0 -1 1 -1 -1
ceiling( v )
[1] -1 0 0 1 1 -1 0 0 2 0 1 0 2 0 0
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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